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Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 39, 2022 No. 1
291-295

Multi-layer weight and lightweight improved optical flow estimation algorithm based on PWC-Net

Hu Yixuan
Wu Fei
Xiong Yujie
Shanghai University of Engineering Science, Shanghai 201620, China
DOI: 10.19734/j.issn.1001-3695.2021.05.0204

Abstract

To solve the problem of insufficient real-time performance of existing optical flow estimation methods, this paper proposed a lightweight improved PSC-NET model with deep separable convolution(depth pyramid, warping and cost volume, DS-PWC). One of the improvements was decoupling the conventional two-dimensional convolutional network layer into a deep separable convolutional layer. The other one was adding a weight coefficient based on the number of layers in the pyramid layer by DS-PWC, which greatly reduced the number of model parameters in the network structure without loss of precision. In addition, in the training process, the paper applied data enhancement technologies such as I+ORE to further improve the generalization ability of estimation and prediction results. The experimental results show that the DS-PWC model was tested in the dataset and the operating efficiency reaches about 58 fps while maintaining the quality. To verify the effectiveness of the algorithm, this paper carried out the ablation experiments of model structure and data enhancement. The results verify the effectiveness of the DS-PWC model.

Foundation Support

上海市科技学术委员会重点项目(18511101600)
国家自然科学基金资助项目(62006150,61802251)
上海青年科技英才扬帆计划资助项目(19YF1418400)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2021.05.0204
Publish at: Application Research of Computers Printed Article, Vol. 39, 2022 No. 1
Section: Technology of Graphic & Image
Pages: 291-295
Serial Number: 1001-3695(2022)01-052-0291-05

Publish History

[2022-01-05] Printed Article

Cite This Article

胡毅轩, 吴飞, 熊玉洁. 基于PWC-Net的多层权值和轻量化改进光流估计算法 [J]. 计算机应用研究, 2022, 39 (1): 291-295. (Hu Yixuan, Wu Fei, Xiong Yujie. Multi-layer weight and lightweight improved optical flow estimation algorithm based on PWC-Net [J]. Application Research of Computers, 2022, 39 (1): 291-295. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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